English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We introduce a new sufficient statistic for the population parameter vectorby allowing for the sampling design to first be selected at random amongst aset of candidate sampling designs. In contrast to the traditional approach insurvey sampling, we achieve this by defining the observed data to include amention of the sampling design used for the data collection aspect of thestudy. We show that the reduced data consisting of the unit labels togetherwith their corresponding responses of interest is a sufficient statistic underthis setup. A Rao-Blackwellization inference procedure is outlined and it isshown how averaging over hypothetical observed data outcomes results inimproved estimators; the improved strategy includes considering all possiblesampling designs in the candidate set that could have given rise to the reduceddata. Expressions for the variance of the Rao-Blackwell estimators are alsoderived. The results from two simulation studies are presented to demonstratethe practicality of our approach. A discussion on how our approach can beuseful when the analyst has limited information on the data collectionprocedure is also provided.

A Broadened Approach for Improved Estimation in Survey Sampling